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At least 613 records · Page 34Linked to original sources
PubMed1994

Three-dimensional pharmacophores from binding data.

The application of HASL (hypothetical active site lattice) methodology has been successfully extended to generate putative pharmacophoric patterns in three dimensions capable of quantitatively predicting binding activity. The transformation of a HASL model to a pharmacophore is illustrated using pKi values published for 84 HIV-1 protease inhibitors. Starting with a HASL model generated at 2.00 A and containing 899 lattice points, a selective trimming process was used to identify significant lattice points. In this manner, a set of 11 points was found which represents a potential pharmacophoric pattern and predicts the pKi activity of the 84-inhibitor set with a correlation (r2) of 0.827. Furthermore, the locations of these points were found to coincide with a number of strategic binding areas within the known active site structure HIV-1 protease, thus providing a physical confirmation of their relevancy.

Binding Sites↗
PubMed1987

ISMOD: an all-subsets regression program for generalized linear models. I. Statistical and computational background.

This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log-logistic, log-normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and has an all-subsets regression feature. This paper describes the models implemented and gives statistical background; Part II describes the ISMOD system and presents examples of its application.

Biometry↗
PubMed2005

Predictive models for hERG potassium channel blockers.

We report here a general method for the prediction of hERG potassium channel blockers using computational models generated from correlation analyses of a large dataset and pharmacophore-based GRIND descriptors. These 3D-QSAR models are compared favorably with other traditional and chemometric based HQSAR methods.

Anti-Arrhythmia Agents↗
PubMed1991

A distributed-parameter model of the myelinated nerve fiber.

This paper presents a new model for the characterization of electrical activity in the nodal, paranodal and internodal regions of isolated amphibian and mammalian myelinated nerve fibers. It differs from previous models in the following ways: (1) in its ability to incorporate detailed anatomical and electrophysiological data; (2) in its approach to the myelinated nerve fiber as a multi-axial cable; and (3) in the numerical algorithm used to obtain distributed model equation solutions for potential and current. The morphometric properties are taken from detailed electron microscopic anatomical studies (Berthold & Rydmark, 1983a, Experientia 39, 964-976). The internodal axolemma is characterized as an excitable membrane and model-generated nodal and internodal membrane action potentials are presented. A system of describing equations for the equivalent network model is derived, based on the application of Kirchoff's Current Law, which take the form of multiple cross-coupled parabolic partial differential equations. An implicit numerical integration method is developed and the numerical solution implemented on a parallel processor. Non-uniform spatial step sizes are used, enabling detailed representation of the nodal region while minimizing the number of total segments necessary to represent the overall fiber. Conduction velocities of 20.2 m sec-1 at 20 degrees C for a 15 microns diameter amphibian fiber and 57.6 m sec-1 at 37 degrees C for a 17.5 microns diameter mammalian fiber are achieved, which agrees qualitatively with published experimental data at similar temperatures (Huxley & Stämpfli, 1949, J. Physiol., Lond. 108, 315-339; Rasminsky, 1973, Arch, Neurol. 28, 287-292). The simulation results demonstrate the ability of this model to produce detailed representations of the transaxonal, transmyelin and transfiber potentials and currents, as well as the longitudinal extra-axonal, periaxonal and intra-axonal currents. Also indicated is the potential contribution of the paranodal axolemma to nodal activity as well as the presence of significant longitudinal currents in the periaxonal space adjacent to the node of Ranvier.

Action Potentials↗
PubMed2003

The relation between depression and anxiety: an evaluation of the tripartite, approach-withdrawal and valence-arousal models.

Epidemiological studies have consistently reported that depressive and anxiety disorders co-occur frequently. This paper reviews the evidence for three models that have been proposed to explain the relation between these two conditions-the tripartite, the approach-withdrawal, and valence-arousal models. Specifically, we focus on predictions that the three models generate for cross-sectional studies, prospective and family/twin studies of personality, and EEG studies. In sum, no model was strongly supported across all types of studies, though specific aspects of each model were. Because of the heterogeneity of depression and anxiety disorders, a model with 2-4 factors or dimensions may not be sufficient to explain the relation between the two conditions.

Anxiety Disorders↗
PubMed2005

An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus.

The primary impediment to formulating a general theory for adaptive evolution has been the unknown distribution of fitness effects for new beneficial mutations. By applying extreme value theory, Gillespie circumvented this issue in his mutational landscape model for the adaptation of DNA sequences, and Orr recently extended Gillespie's model, generating testable predictions regarding the course of adaptive evolution. Here we provide the first empirical examination of this model, using a single-stranded DNA bacteriophage related to phiX174, and find that our data are consistent with Orr's predictions, provided that the model is adjusted to incorporate mutation bias. Orr's work suggests that there may be generalities in adaptive molecular evolution that transcend the biological details of a system, but we show that for the model to be useful as a predictive or inferential tool, some adjustments for the biology of the system will be necessary.

Adaptation, Biological↗
PubMed2005

A density-functional model of the dispersion interaction.

We have recently introduced [J. Chem. Phys. 122, 154104 (2005)] a simple parameter-free model of the dispersion interaction based on the instantaneous in space, dipole moment of the exchange hole. The model generates remarkably accurate interatomic and intermolecular C6 dispersion coefficients, and geometries and binding energies of intermolecular complexes. The model involves, in its original form, occupied Hartree-Fock or Kohn-Sham orbitals. Here we present a density-functional reformulation depending only on total density, the gradient and Laplacian of the density, and the kinetic-energy density. This density-functional model performs as well as the explicitly orbital-dependent model, yet offers obvious computational advantages.

Journal Article↗
PubMed2005

GlyProt: in silico glycosylation of proteins.

GlyProt (http://www.glycosciences.de/glyprot/) is a web-based tool that enables meaningful N-glycan conformations to be attached to all the spatially accessible potential N-glycosylation sites of a known three-dimensional (3D) protein structure. The probabilities of physicochemical properties such as mass, accessible surface and radius of gyration are calculated. The purpose of this service is to provide rapid access to reliable 3D models of glycoproteins, which can subsequently be refined by using more elaborate simulations and validated by comparing the generated models with experimental data.

Computational Biology↗
PubMed2006

In silico simulations suggest that Th-cell development is regulated by both selective and instructive mechanisms.

Th-cell differentiation is highly influenced by the local cytokine environment. Although cytokines such as IL-12 and IL-4 are known to polarize the Th-cell response towards Th1 or Th2, respectively, it is not known whether these cytokines instruct the developmental fate of uncommitted Th cells or select cells that have already been committed through a stochastic process. We present an individual based model that accommodates both stochastic and deterministic processes to simulate the dynamic behaviour of selective versus instructive Th-cell development. The predictions made by each model show distinct behaviours, which are compared with experimental observations. The simulations show that the instructive model generates an exclusive Th1 or Th2 response in the absence of an external cytokine source, whereas the selective model favours coexistence of the phenotypes. A hybrid model, including both instructive and selective development, shows behaviour similar to either the selective or the instructive model dependent on the strength of activation. The hybrid model shows the closest qualitative agreement with a number of well-established experimental observations. The predictions by each model suggest that neither pure selective nor instructive Th development is likely to be functional as exclusive mechanisms in Th1/Th2 development.

Animals↗
PubMedDate not supplied

A peripartum neurologic event: shooting from the hip.

We have shown that a simplified model, generated quickly in response to an emergency consultation, may provide useful insights in certain situations. A more developed model was useful in verifying these insights. Because the more complex model considered a longer time horizon than the simple model, it allows us to consider questions regarding long-term benefits of aneurysm repair. When modeling any problem, the most important reason for performing decision analysis is to gain insight from analyzing the clinical setting and from constructing the model. The quantitative results are usually of only minor importance. However, our most important insights are sometimes gained by looking beyond the quantitative level to understand the interactions of various effects within the model. In this case, it was those insights that were of the greatest benefit to the patient in arriving at a decision to have cerebral arteriography.

Adult↗
PubMed1995

Mechanical control of swimming speed: stiffness and axial wave form in undulating fish models

The purpose of this study was to investigate the mechanical control of speed in steady undulatory swimming. The roles of body flexural stiffness, driving frequency and driving amplitude were examined; these variables were chosen because of their importance in vibration theory and their hypothesized functions in undulatory swimming. Using a mold of a pumpkinseed sunfish Lepomis gibbosus, we cast three-dimensional vinyl models of four different flexural stiffnesses. We swam the models in a flow tank and powered them via the input of an oscillating sinusoidal bending couple in the horizontal plane at the posterior margin of the neurocranium. To simulate the hydrodynamic conditions of steady swimming, drag and thrust acting on the model were balanced by adjusting flow speed. Under these conditions, the actuated models generated traveling waves of bending. At steady speeds, the motions of the ventral and lateral surfaces of the model were video-taped and analyzed to yield the following response variables: tail-beat amplitude, propulsive wavelength, wave speed and depth of the trailing edge of the caudal fin. Experimental results showed that changes in body flexural stiffness can control propulsive wavelength, wave speed, Froude efficiency and, in consequence, swimming speed. Driving frequency can control tail-beat amplitude, propulsive wavelength, Froude efficiency, relative rate of working and, in consequence, swimming speed. Although there is no significant correlation between rostral amplitude and swimming speed, rostral amplitude can control swimming speed indirectly by controlling tail-beat amplitude and relative power. Compared with live sunfish using undulatory waves at the same speed, models have a lower Froude efficiency. On the basis of the mechanical control of swimming speed in model sunfish, we predict that, in order to swim at fast speeds, live sunfish increase the flexural stiffness of their bodies by a factor of two relative to their passive body stiffness.

Journal Article↗
PubMed2001

The brain decade in debate: II. Panic or anxiety? From animal models to a neurobiological basis.

This article is a transcription of an electronic symposium sponsored by the Brazilian Society of Neuroscience and Behavior (SBNeC). Invited researchers from the European Union, North America and Brazil discussed two issues on anxiety, namely whether panic is a very intense anxiety or something else, and what aspects of clinical anxiety are reproduced by animal models. Concerning the first issue, most participants agreed that generalized anxiety and panic disorder are different on the basis of clinical manifestations, drug response and animal models. Also, underlying brain structures, neurotransmitter modulation and hormonal changes seem to involve important differences. It is also common knowledge that existing animal models generate different types of fear/anxiety. A challenge for future research is to establish a good correlation between animal models and nosological classification.

Anti-Anxiety Agents↗
PubMed2005

Use of diagnosis-based risk adjustment models to predict individual health care expenditure under the National Health Insurance system in Taiwan.

BACKGROUND AND PURPOSE: Diagnostic information has been extensively studied and employed in the prediction of risk adjusted capitation payments in some countries. Nevertheless, few studies have been dedicated to the development of diagnosis-based risk adjusters in Taiwan. The purposes of this study were to develop outpatient diagnosis-based risk adjusters for a model of Taiwan's National Health Insurance (NHI) system and to evaluate the predictability of the risk adjustment models generated utilizing these adjusters. METHODS: Using a 2% random sample of 371,620 NHI enrollees, 5 risk adjustment models--i.e., demographic, inpatient diagnostic information outpatient diagnostic information, full diagnostic information, and prior utilization models--were evaluated with respect to predictive R2 and predictive ratios. While inpatient diagnosis-based risk adjusters were borrowed from previous research, outpatient diagnosis-based risk adjusters, referred to as Taiwan Ambulatory Spending Groups (TASGs), were developed based on 1996 claims data. RESULTS: The values of predictive R2 for the 5 risk adjustment models showed that the inclusion of outpatient diagnostic information considerably improved the predictability of the risk adjustment models for Taiwan's NHI system. Moreover, the predictive ratios revealed that the full diagnostic information model would reimburse different risk subgroups more fairly than the demographic, inpatient diagnostic information, and outpatient diagnostic information models and also outperform the prior utilization model with respect to disease risk groups. CONCLUSIONS: The risk adjustment model including the TASG risk adjusters can significantly improve predictability and can be employed to assess the NHI's current and proposed reform measures.

Capitation Fee↗
PubMed1994

Modeling Alzheimer's disease in transgenic mice.

Alzheimer's disease is a common neurodegenerative disorder of unknown etiology characterized by the accumulation of beta amyloid plaques and neurofibrillary tangles in the brain. Attempts have been made to engineer an animal model of the disease using a variety of transgenic approaches. So far the models have only been partially successful. The methods used and the models generated are discussed.

Alzheimer Disease↗
PubMed2005

Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software.

BACKGROUND: There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal. RESULTS: We have created 3DSpi, a multi-agent based software that we used to explore the generation of multi-protein dynamic structures. Being based on a very restricted set of parameters, it is perfectly suited for exploring the minimal set of rules needed to generate large multi-protein structures. It can therefore be used to test the hypothesis that such structures are formed and maintained by principles of self-organization. We observed that multi-protein structures emerge and that the system behavior is very robust, in terms of the number and size of the structures generated. Furthermore, the generated structures very closely mimic spatial organization of real life multi-protein structures. CONCLUSION: The behavior of 3DSpi confirms the considerable potential of MAS for modeling subcellular structures. It demonstrates that robust multi-protein structures can emerge using a restricted set of parameters and allows the exploration of the dynamics of such structures. A number of easy-to-implement modifications should make 3DSpi the virtual simulator of choice for scientists wishing to explore how topology interacts with time, to regulate the function of interacting proteins in living cells.

Cellular Structures↗
PubMed2003

Consensus alignment for reliable framework prediction in homology modeling.

MOTIVATION: Even the best sequence alignment methods frequently fail to correctly identify the framework regions for which backbones can be copied from the template into the target structure. Since the underprediction and, more significantly, the overprediction of these regions reduces the quality of the final model, it is of prime importance to attain as much as possible of the true structural alignment between target and template. RESULTS: We have developed an algorithm called Consensus that consistently provides a high quality alignment for comparative modeling. The method follows from a benchmark analysis of the 3D models generated by ten alignment techniques for a set of 79 homologous protein structure pairs. For 20-to-40% of the targets, these methods yield models with at least 6 A root mean square deviation (RMSD) from the native structure. We have selected the top five performing methods, and developed a consensus algorithm to generate an improved alignment. By building on the individual strength of each method, a set of criteria was implemented to remove the alignment segments that are likely to correspond to structurally dissimilar regions. The automated algorithm was validated on a different set of 48 protein pairs, resulting in 2.2 A average RMSD for the predicted models, and only four cases in which the RMSD exceeded 3 A. The average length of the alignments was about 75% of that found by standard structural superposition methods. The performance of Consensus was consistent from 2 to 32% target-template sequence identity, and hence it can be used for accurate prediction of framework regions in homology modeling.

Algorithms↗
PubMedDate not supplied

Predictive models of hepatotoxicity using gene expression data from primary rat hepatocytes.

With the aim of evaluating the usefulness of an in vitro system for assessing the potential hepatotoxicity of compounds, the paper describes several methods of obtaining mathematical models for the prediction of compound-induced toxicity in vivo. These models are based on data derived from treating rat primary hepatocytes with various compounds, and thereafter using microarrays to obtain gene expression 'profiles' for each compound. Predictive models were constructed so as to reduce the number of 'probesets' (genes) required, and subjected to rigorous cross-validation. Since there are a number of possible approaches to derive predictive models, several distinct modelling strategies were applied to the same data set, and the outcomes were compared and contrasted. While all the strategies tested showed significant predictive capability, it was interesting to note that the different approaches generated models based on widely disparate probesets. This implies that while these models may be useful in ascribing relative potential toxicity to compounds, they are unlikely to provide significant information on underlying toxicity mechanisms. Improved predictivity will be obtained through the generation of more comprehensive gene expression databases, covering more 'toxicity space', and by the development of models that maximize the observation, and combination, of individual differences between compounds.

Animals↗
PubMed2000

Three-dimensional model of the extracellular domain of the type 4a metabotropic glutamate receptor: new insights into the activation process.

Metabotropic glutamate receptors (mGluRs) belong to the family 3 of G-protein-coupled receptors. On these proteins, agonist binding on the extracellular domain leads to conformational changes in the 7-transmembrane domains required for G-protein activation. To elucidate the structural features that might be responsible for such an activation mechanism, we have generated models of the amino terminal domain (ATD) of type 4 mGluR (mGlu4R). The fold recognition search allowed the identification of three hits with a low sequence identity, but with high secondary structure conservation: leucine isoleucine valine-binding protein (LIVBP) and leucine-binding protein (LBP) as already known, and acetamide-binding protein (AmiC). These proteins are characterized by a bilobate structure in an open state for LIVBP/LBP and a closed state for AmiC, with ligand binding in the cleft. Models for both open and closed forms of mGlu4R ATD have been generated. ACPT-I (1-aminocyclopentane 1,3,4-tricarboxylic acid), a selective agonist, has been docked in the two models. In the open form, ACPT-I is only bound to lobe I through interactions with Lys74, Arg78, Ser159, and Thr182. In the closed form, ACPT-I is trapped between both lobes with additional binding to Tyr230, Asp312, Ser313, and Lys317 from lobe II. These results support the hypothesis that mGluR agonists bind a closed form of the ATDs, suggesting that such a conformation of the binding domain corresponds to the active conformation.

Amino Acid Sequence↗